Integrated Biomarkers to Characterize Breast Cancer Risk

描述（由申请人提供）：本提案的目的是开发、验证和整合新的生物标志物，以表征患乳腺癌、患乳腺癌或进展乳腺癌的风险。我们已经组建了一支由学术和行业研究人员组成的优秀多学科团队，他们正在使用分子和细胞技术进行生物标志物的开发。我们将利用强大的临床资源，包括独特的回顾性和前瞻性数据集，进一步开发和评估它们，并将它们相互整合（交叉验证）并纳入临床决策（建模）。拟议的研究试图重新定义从传统乳腺癌筛查到联合检测/生物学表征/风险预测的范式。我们的假设是：1)SNP（种系）和蛋白质组学（血清）谱可以确定乳腺癌风险并检测早期癌症，并可能结合起来作为分层筛查策略；2)有前途的指示进展和转移风险的生物标志物，包括基于组织的表达谱和循环肿瘤细胞（CTCs）的检测，应该直接进行比较和整合，以最大限度地了解表型和风险；3)生物标志物的联合分析不仅效率更高，而且可能为优化临床应用提供综合策略。为了完成我们的工作，我们提出了4个项目：项目1：开发基于SNP和血清蛋白质组学的癌症检测谱（原发性和继发性）和风险谱，在可触及乳房x光检查异常的临床评估背景下；项目2：利用回顾性数据集开发基于石蜡的表达谱来预测疾病进展的风险（盖伊医院：自然史人群，随访25年，未进行全身治疗；UCSF综合微转移/CTC数据集；UCSF SPORE DCIS数据集）；项目3：开发和验证基于CTC的分析，包括CTC检测的领先方法；与基于组织的生物标志物交叉验证CTC数据；开发CTCs的分子谱分析方法；项目4：在一项前瞻性临床研究中评估有前景的生物标志物，以交叉验证检测方法，并整合到反映检测到的癌症生物学特性的预测结果模型中。

DESCRIPTION (provided by applicant): The purpose of this proposal is to develop, validate and integrate novel biomarkers to characterize the risk of getting, having, or progressing with breast cancer. We have assembled a superb multidisciplinary team of academic and industry investigators who are using molecular and cell based technologies for biomarker development. We will further develop and evaluate them using powerful clinical resources, including unique retrospective and prospective data sets, and will integrate them with each other (cross validation) and into the context of clinical decision (modeling). The proposed studies attempt to redefine the paradigm from conventional breast cancer screening to combined detection/biological characterization/risk projection. Our hypotheses are that: 1) SNP (germline) and proteomic (serum) profiles can define breast cancer risk and detect early cancer, and may be combined for a tiered screening strategy; 2) Promising biomarkers indicative of risk of progression and metastasis, including tissue-based expression profiling and detection of circulating tumor cells (CTCs), should be directly compared as well as integrated to maximize information about phenotypes and risk; and 3) Combined analysis of biomarkers is not only more efficient but may lead to integrated strategies for optimal clinical application. In order to accomplish our work we propose 4 projects: Project 1: Develop SNP- and serum proteomics-based profiles for cancer detection (primary and secondary) and risk profiling in the context of clinical evaluation of palpable and mammographic abnormalities; Project 2: Develop paraffin based expression profiles to predict risk of disease progression using retrospective datasets (Guy's Hospital: natural history population with 25 yr follow-up and no systemic therapy; UCSF comprehensive micrometastases/CTC data set; UCSF SPORE DCIS data set); Project 3: Develop and validate CTC-based assays, including leading approaches for CTC detection; cross-validate CTC data with tissue-based biomarkers; and develop methods for molecular profiling of CTCs; Project 4: Evaluate promising biomarkers in a prospective clinical study for cross validation of assays and integration into predictive outcome models that reflect the biological properties of the cancer detected.